Balance Between Collecting Data and Connecting to Data

Because data is the most valuable resource in the digital business era, collecting it using only a centralized management approach is no longer viable. Data and analytics leaders need to take an aggressive approach that creates an appropriate balance between data collection and data connection.

Key Challenges

• Data is distributed between cloud and premises, and hybrid deployments are becoming the default approach.
• The scale and pace of creation of data, as well as the need to harness it in real time, make it impossible to always collect data and then process it for a single value proposition or use case.
• As organizations prioritize operational efficiency and analytics, these two forces are making organizations rethink their data management strategies and investments.
• Data governance and regulatory requirements need to span all use cases and data distribution is further challenging centralized data governance approaches.
• Deploying different data management capabilities for each individual use cases leads to unmanageable implementations and escalating operating costs.

Recommendations

Data and analytics leaders who are focused on modernizing data management capabilities must:

• Master the components of data management for flexible deployments. It will adapt data architecture to distributed data and changing demands.
• Use bimodal approaches to meet operational uses of data, experimental and innovative uses of data, and support a smooth transition from one to the other.
• Rethink data governance by focusing on transparency and trust.
• Adapt your data management approaches to address emerging citizen roles.
• Expect implementation trade offs (and be ready to overcome them) as mismatches between the initial requirements for data management projects and ongoing expectations can be extreme, and could force a rethink of the implementation.

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